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KDD
2004
ACM
170views Data Mining» more  KDD 2004»
15 years 11 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
109
Voted
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
15 years 11 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
KDD
2003
ACM
124views Data Mining» more  KDD 2003»
15 years 11 months ago
Information-theoretic co-clustering
Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingenc...
Inderjit S. Dhillon, Subramanyam Mallela, Dharmend...
94
Voted
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
15 years 11 months ago
Mining data records in Web pages
A large amount of information on the Web is contained in regularly structured objects, which we call data records. Such data records are important because they often present the e...
Bing Liu, Robert L. Grossman, Yanhong Zhai
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
15 years 11 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...